SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 4451–4500 of 10817 papers

TitleStatusHype
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool EmbeddingsCode2
Eye-SpatialNet: Spatial Information Extraction from Ophthalmology Notes—0
Exploring the Viability of Synthetic Query Generation for Relevance Prediction—0
Self-QA: Unsupervised Knowledge Guided Language Model AlignmentCode3
Evaluation of medium-large Language Models at zero-shot closed book generative question answering—0
S^3HQA: A Three-Stage Approach for Multi-hop Text-Table Hybrid Question AnsweringCode1
Cue-CoT: Chain-of-thought Prompting for Responding to In-depth Dialogue Questions with LLMsCode1
Surgical-VQLA: Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic SurgeryCode1
Enhancing Vision-Language Pre-Training with Jointly Learned Questioner and Dense CaptionerCode1
Empower Large Language Model to Perform Better on Industrial Domain-Specific Question AnsweringCode1
LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and GenerationCode1
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing—0
Graphologue: Exploring Large Language Model Responses with Interactive Diagrams—0
Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsCode1
Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature—0
Writing your own book: A method for going from closed to open book QA to improve robustness and performance of smaller LLMs—0
mLongT5: A Multilingual and Efficient Text-To-Text Transformer for Longer SequencesCode1
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
MedBLIP: Bootstrapping Language-Image Pre-training from 3D Medical Images and TextsCode1
Large Language Models can be Guided to Evade AI-Generated Text DetectionCode1
Tree of Thoughts: Deliberate Problem Solving with Large Language ModelsCode5
What You See is What You Read? Improving Text-Image Alignment EvaluationCode1
Can Language Models Solve Graph Problems in Natural Language?Code1
IMAD: IMage-Augmented multi-modal DialogueCode0
TG-VQA: Ternary Game of Video Question Answering—0
Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries—0
An Empirical Study on the Language Modal in Visual Question Answering—0
PMC-VQA: Visual Instruction Tuning for Medical Visual Question AnsweringCode1
Probing the Role of Positional Information in Vision-Language Models—0
PaLM 2 Technical Report—0
Iterative Adversarial Attack on Image-guided Story Ending Generation—0
A Video Is Worth 4096 Tokens: Verbalize Videos To Understand Them In Zero ShotCode0
Large Language Models are Built-in Autoregressive Search EnginesCode1
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech TranslationCode0
xPQA: Cross-Lingual Product Question Answering across 12 LanguagesCode1
StructGPT: A General Framework for Large Language Model to Reason over Structured DataCode2
Towards Expert-Level Medical Question Answering with Large Language ModelsCode1
Is a Video worth n n Images? A Highly Efficient Approach to Transformer-based Video Question Answering—0
Semantic Composition in Visually Grounded Language Models—0
It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance—0
Exploring In-Context Learning Capabilities of Foundation Models for Generating Knowledge Graphs from Text—0
Capturing Humans' Mental Models of AI: An Item Response Theory ApproachCode0
MeeQA: Natural Questions in Meeting TranscriptsCode0
KEPR: Knowledge Enhancement and Plausibility Ranking for Generative Commonsense Question AnsweringCode0
Motion Question Answering via Modular Motion ProgramsCode1
Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence ModelingCode1
Question-Answering System Extracts Information on Injection Drug Use from Clinical NotesCode0
Semantic-aware Dynamic Retrospective-Prospective Reasoning for Event-level Video Question Answering—0
Learning to Generalize for Cross-domain QACode0
Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified